Suppression of zinc dendrites in zinc electrode power cells

Addition of various tetraalkyl quarternary ammonium salts, to alkaline zincate electrolyte of cell, prevents formation of zinc dendrites during charging of zinc electrode. Electrode capacity is not impaired and elimination of dendrites prolongs cell life

Clonal analysis of meningococci during a 26 year period prior to the introduction of meningococcal serogroup C vaccines

Meningococcal disease remains a public health burden in the UK and elsewhere. Invasive Neisseria meningitidis, isolated in Scotland between 1972 and 1998, were characterised retrospectively to examine the serogroup and clonal structure of the circulating population. 2607 isolates causing invasive disease were available for serogroup and MLST analysis whilst 2517 were available for multilocus sequence typing (MLST) analysis only. Serogroup distribution changed from year to year but serogroups B and C were dominant throughout. Serogroup B was dominant throughout the 1970s and early 1980s until serogroup C became dominant during the mid-1980s. The increase in serogroup C was not associated with one particular sequence type (ST) but was associated with a number of STs, including ST-8, ST-11, ST-206 and ST-334. This is in contrast to the increase in serogroup C disease seen in the 1990s that was due to expansion of the ST-11 clonal complex. While there was considerable diversity among the isolates (309 different STs among the 2607 isolates), a large proportion of isolates (59.9%) were associated with only 10 STs. These data highlight meningococcal diversity over time and the need for ongoing surveillance during the introduction of new meningococcal vaccines

The Positive and Negative Experiences of 342 Antidepressant Users

Most efficacy and safety studies about medications adopt a quantitative approach, testing specific hypotheses with restricted samples. This online survey provides additional insights by directly asking people open questions. Thematic analysis was used to explore the responses of 342 antidepressant users to “Is there anything else you would like to tell us about your experience of taking medication”. 59 (17.3%) made exclusively positive comments, 146 (42.7%) purely negative comments and 137 (40.0%) offered a mixture of positive and negative. Positive themes included: Daily Coping, Life-Changing/Saving and Stepping Stone. Negative themes included: Physical Adverse Effects, Emotional and Cognitive Blunting, and Withdrawal Effects. Many participants also commented on relationships with prescribers. Collaboration was particularly valued. Negative sub-themes included failings in relation to information (especially about adverse effects and withdrawal), support, and alternatives. Clinicians have a duty to inform potential antidepressant users about positive and adverse effects, including withdrawal effects

Longitudinal LASSO: Jointly Learning Features and Temporal Contingency for Outcome Prediction

Longitudinal analysis is important in many disciplines, such as the study of behavioral transitions in social science. Only very recently, feature selection has drawn adequate attention in the context of longitudinal modeling. Standard techniques, such as generalized estimating equations, have been modified to select features by imposing sparsity-inducing regularizers. However, they do not explicitly model how a dependent variable relies on features measured at proximal time points. Recent graphical Granger modeling can select features in lagged time points but ignores the temporal correlations within an individual's repeated measurements. We propose an approach to automatically and simultaneously determine both the relevant features and the relevant temporal points that impact the current outcome of the dependent variable. Meanwhile, the proposed model takes into account the non-{\em i.i.d} nature of the data by estimating the within-individual correlations. This approach decomposes model parameters into a summation of two components and imposes separate block-wise LASSO penalties to each component when building a linear model in terms of the past $\tau$ measurements of features. One component is used to select features whereas the other is used to select temporal contingent points. An accelerated gradient descent algorithm is developed to efficiently solve the related optimization problem with detailed convergence analysis and asymptotic analysis. Computational results on both synthetic and real world problems demonstrate the superior performance of the proposed approach over existing techniques.Comment: Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. ACM, 201

Organic source of nitrogen trials & miscellaneous trials.

1. Nitrogen sources Badgingarra 85BA3 Organic Source of Nitrogen 8SBA4 Interaction of Organic and Inorganic Nitrogen sources 85BAS Miscellaneous Organic Nitrogen Sources 85BA39 Times and Levels of Inorganic Nitrogen Application Lancelin 85M02 Organic sources of nitrogen 85M03 Interaction of Organic and Inorganic Nitrogen Sources 85M04 Miscellaneous Organic Nitrogen Sources 85MOS3 Times and Levels of Inorganic Nitrogen Application Meckering 85N01 Organic Sources of Nitrogen 85N03 Miscellaneous Organic Nitrogen Sources 85NOS9 Times and Levels of Inorganic Nitrogen Application 2. Miscellaneous trials 84M6 Rates of Nitrogen on Wheat - CSIRO Megatrial (E. Harvey) 85M4 Nitrogen and Water on Wheat (with M. Mason) 83WH29 Residual Effects of Crop and Pasture Species on Second Wheat Crop 82WH2 Residual Value of Ripping (4th Year

Estimating stellar oscillation-related parameters and their uncertainties with the moment method

The moment method is a well known mode identification technique in asteroseismology (where `mode' is to be understood in an astronomical rather than in a statistical sense), which uses a time series of the first 3 moments of a spectral line to estimate the discrete oscillation mode parameters l and m. The method, contrary to many other mode identification techniques, also provides estimates of other important continuous parameters such as the inclination angle alpha, and the rotational velocity v_e. We developed a statistical formalism for the moment method based on so-called generalized estimating equations (GEE). This formalism allows the estimation of the uncertainty of the continuous parameters taking into account that the different moments of a line profile are correlated and that the uncertainty of the observed moments also depends on the model parameters. Furthermore, we set up a procedure to take into account the mode uncertainty, i.e., the fact that often several modes (l,m) can adequately describe the data. We also introduce a new lack of fit function which works at least as well as a previous discriminant function, and which in addition allows us to identify the sign of the azimuthal order m. We applied our method to the star HD181558, using several numerical methods, from which we learned that numerically solving the estimating equations is an intensive task. We report on the numerical results, from which we gain insight in the statistical uncertainties of the physical parameters involved in the moment method.Comment: The electronic online version from the publisher can be found at http://www.blackwell-synergy.com/doi/abs/10.1111/j.1467-9876.2005.00487.

Towards measures of the eradicability of rain-splashed crop diseases

Controlling rain-splashed crop diseases is an extremely difficult task. Their spread is a complicated process and large-scale field surveys to determine the extent of an incursion over a large area are often economically intractable. A failed attempt at control or eradication of a pathogen can be very costly. In 1996 there was a major incursion of lupin anthracnose in Western Australia, which crippled the albus lupin industry. At the time of the outbreak a wide-spread survey was undertaken to estimate the extent of the incursion. A containment protocol involving broad-scale crop destruction was put into place with the view of eradicating the disease. This eradication attempt subsequently failed due to wild lupins acting as a reservoir for the disease from road verges and non-arable land outside the cropping area. There was also evidence of long distance dispersal vectors such as native budworm. Had all the relevant information related to spread and spatial habitat suitability been collected and taken into account, the decision to destroy the crops may not have been made and significant economic losses to growers may have been avoided. Estimates of the current extent of an incursion based solely on incomplete empirical data are likely to be inaccurate, as are predictions of the future trajectory of an incursion that do not take into account all available information. Therefore any control or eradication attempt based on these estimates and predictions may be ineffective. Simulation modelling is an important method for making the best use of all available empirical data and integrating all available knowledge to predict the spread of rain-splashed crop diseases. With this prediction, an evaluation of the potential success of control or eradication measures may be estimated. This study describes a model that was built to simulate a situation analogous to that of the 1996 lupin anthracnose incursion in Western Australia, for the purpose of identifying general indicators of the eradicability of rain-splashed crop diseases. We extended the spatiotemporal model AnthracnoseTracer to simulate the spread of lupin anthracnose in a heterogeneous paddock environment analogous to the 1996 conditions. Three control methods aimed at eradication were investigated. A simple detection model was assumed, where the probability of detecting the disease is dependent on the level of passive surveillance and the detectability of the disease. As part of the preliminary analysis contained in this paper we investigated two scenarios to identify potential indicators of eradicability, based on the time taken to detect the disease. Our preliminary results indicate that rain-splashed pathogens are extremely difficult to eradicate and the chance of successful eradication appears strongly dependent on the level of surveillance of the susceptible areas and the detectability of the disease. The level of surveillance and detectability of the disease may both serve as general indicators of eradicability for rain-splashed crop diseases. We discuss further modelling analyses to be carried out to refine these indicators

Inhibition of double-strand break non-homologous end-joining by cisplatin adducts in human cell extracts

The effect of cis-diaminedichloroplatinum(II) (cisplatin) DNA damage on the repair of double-strand breaks by non-homologous end-joining (NHEJ) was determined using cell-free extracts. NHEJ was dramatically decreased when plasmid DNA was damaged to contain multiple types of DNA adducts, along the molecule and at the termini, by incubation of DNA with cisplatin; this was a cisplatin concentration-dependent effect. We investigated the effect a single GTG cisplatination site starting 10 bp from the DNA termini would have when surrounded by the regions of AT-rich DNA which were devoid of the major adduct target sequences. Cisplatination of a substrate containing short terminal 13–15 bp AT-rich sequences reduced NHEJ to a greater extent than that of a substrate with longer (31–33 bp) AT-rich sequences. However, cisplatination at the single GTG site within the AT sequence had no significant effect on NHEJ, owing to the influence of additional minor monoadduct and dinucleotide adduct sites within the AT-rich region and owing to the influence of cisplatination at sites upstream of the AT-rich regions. We then studied the effect on NHEJ of one cis-[Pt(NH(3))(2){d(GpTpG)-N7(1),-N7(3)} [abbreviated as 1,3-d(GpTpG)] cisplatin adduct in the entire DNA molecule, which is more reflective of the situation in vivo during concurrent chemoradiation. The presence of a single 1,3-d(GpTpG) cisplatin adduct 10 bases from each of the two DNA ends to be joined resulted in a small (30%) but significant decrease in NHEJ efficiency. This process, which was DNA-dependent protein kinase and Ku dependent, may in part explain the radiosensitizing effect of cisplatin administered during concurrent chemoradiation

Robust Estimation for Linear Panel Data Models

In different fields of applications including, but not limited to, behavioral, environmental, medical sciences and econometrics, the use of panel data regression models has become increasingly popular as a general framework for making meaningful statistical inferences. However, when the ordinary least squares (OLS) method is used to estimate the model parameters, presence of outliers may significantly alter the adequacy of such models by producing biased and inefficient estimates. In this work we propose a new, weighted likelihood based robust estimation procedure for linear panel data models with fixed and random effects. The finite sample performances of the proposed estimators have been illustrated through an extensive simulation study as well as with an application to blood pressure data set. Our thorough study demonstrates that the proposed estimators show significantly better performances over the traditional methods in the presence of outliers and produce competitive results to the OLS based estimates when no outliers are present in the data set